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27 lines
1.2 KiB
Python
27 lines
1.2 KiB
Python
import torch
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from diffsynth.pipelines.flux_image import FluxImagePipeline, ModelConfig
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from PIL import Image
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pipe = FluxImagePipeline.from_pretrained(
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torch_dtype=torch.bfloat16,
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device="cuda",
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model_configs=[
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ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="flux1-dev.safetensors"),
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ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder/model.safetensors"),
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ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="text_encoder_2/*.safetensors"),
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ModelConfig(model_id="black-forest-labs/FLUX.1-dev", origin_file_pattern="ae.safetensors"),
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ModelConfig(model_id="InstantX/FLUX.1-dev-IP-Adapter", origin_file_pattern="ip-adapter.bin"),
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ModelConfig(model_id="google/siglip-so400m-patch14-384", origin_file_pattern="model.safetensors"),
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],
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)
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pipe.load_lora(pipe.dit, "models/train/FLUX.1-dev-IP-Adapter_lora/epoch-4.safetensors", alpha=1)
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image = pipe(
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prompt="dog,white and brown dog, sitting on wall, under pink flowers",
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ipadapter_images=Image.open("data/example_image_dataset/1.jpg"),
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height=768, width=768,
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seed=0
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)
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image.save("image_FLUX.1-dev-IP-Adapter_lora.jpg")
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